Java Persistence Performance Illustrated Guide
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Java Persistence Performance Illustrated Guide

About the Book

This book covers the most common and dangerous performance issues related to the persistence layer: Hibernate, JPA, SQL, JDBC and Hazelcast (check out the book sample). Each performance recipe has a short and condensed description and a "handmade" image that will expose the issue and the potential approaches to avoid it.

About the Author

Anghel Leonard
Anghel Leonard

Anghel Leonard is a CA interested in Java performance

Table of Contents

Introduction

SQL

Lifecycle

SQL statement lifecycle

Avoid DDL generation in production

Indexes/statements

Using functions in the WHERE clause

Why the index column order matters

Primary key vs. Unique key

LIKE vs. equal (=)

LIKE wildcards usage

UNION vs. UNION ALL and JOIN flavors

RDBMS Headlines

Scaling

Master-slave replication

Multi-master replication

Sharding

Throughput and response time

Connections

JDBC DriverManager and DataSource

Using a connection pool

Spring post-commit hooks and connection release

Detect database connection leaks

Little's law

Result Set

Limit the result set

Result set scrollability

Transactions

Atomicity (ACID)

Consistency (ACID)

Isolation (ACID)

Durability (ACID)

Transaction rollback

Deadlock

Non-repeatable reads vs. repeatable reads

Two-phase locking (2PL)

Dirty read

Dirty write

Lost update

Phantom read

Read skew

Write skew

Read Uncommitted

Read Committed

Repeatable Reads

Serializable

JPA & Hibernate

Identifiers

Choose between identifiers generation strategies

The equals() and hashCode() methods

The hi/lo algorithm

Hibernate natural id (@NaturalId)

Querying

DTOs

Hibernate simple SELECT

Using Criteria API

Hibernate and SQL native queries

Show and slow SQLs

Spring redundant save() call

Java 8 Date/Time mapping

Store date, time and timestamps in UTC time zone

7 Ways to delete objects with Hibernate

The JDBC, java.sql.Statement

The JDBC, java.sql.PreparedStatement

Fetching and Loading

Hibernate attributes lazy fetching

Hibernate and JPA fetching entities

Hibernate fetching size

Hibernate loading entities

Direct fetching

Fetching a Proxy reference

Populating a child-side parent association via Proxy

Read only data

Index scan in offset and seek (paging)

N+1

Hibernate HINT_PASS_DISTINCT_THROUGH

Streaming results via Java 8 and Spring Data JPA 1.8

Using Optional in entities

Batching

Hibernate batching

Bulk vs. batch

Hibernate setup batching

PostgreSQL (BIG)SERIAL and batching inserts

Flushing

JPA & Hibernate entity state transitions

Hibernate auto flush

Hibernate dirty checking

Hibernate flushing order

JPA @EntityListeners with callbacks

Relationships

The bidirectional @OneToMany association

JPA/Hibernate @MapsId and unidirectional @OneToOne

Using collection relationships

@ElementCollection

@OneToMany association and insert entities

@OneToMany association and delete entities

6 Best practices for one-to-many and many-to-one associations

Many-to-many and cascade type

Unidirectional @ManyToMany

Unidirectional @ManyToMany Persist & Remove

Bidirectional @ManyToMany

The Open Session in View Anti-Pattern

Inheritance

JPA Single Table Inheritance Strategy

JPA Joined Subclass Inheritance Strategy

JPA Table per Class Inheritance Strategy

@MappedSuperclass

Transactions

Read-only transactions in Spring and Hibernate

Hibernate 5.2.10 get connection as needed

Use @Transactional on repository or on service

Use explicit transactions even for read-only statements

Concurrency

Optimistic locking

LockModeType.OPTIMISTIC_FORCE_INCREMENT

LockModeType.PESSIMISTIC_FORCE_INCREMENT

Pessimistic Locking in UPDATE, DELETE and INSERT

Caching

Hibernate second level cache concurrency strategies

Immutable entities and Second Level Cache (SLC)

Exceptions

Hibernate LazyInitializationException

OptimisticLockException

PersistObjectException

AnnotationException

Microservices

Sagas

Anomalies in microservices sagas

Semantic Lock

Commutative Updates

Reread Value

Version File

Hazelcast

IDs

Generating cluster-wide unique IDs

Distributed Map

Hazlecast in-memory format

The 12 IMap performance tips

Concurrency

Hazelcast pessimistic locking

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